{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas as gpd\n",
    "from shapely.geometry import Point\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"]#设置全局变量字体为黑体\n",
    "plt.rcParams[\"axes.unicode_minus\"] = False#设置全局变量正常显示负号"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.read_csv(r'./使用数据/样地坐标.csv',encoding = 'gb2312')\n",
    "df['geometry'] = list(zip(df['lon'],df['lat']))\n",
    "\n",
    "df['geometry'] = df['geometry'].apply(Point)\n",
    "gpd_df = gpd.GeoDataFrame(df)\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "gpd_df.plot(ax = ax,color = 'green')\n",
    "plt.ylabel('经度')\n",
    "plt.xlabel('纬度')\n",
    "plt.text(112.82,31.005,'度')\n",
    "plt.text(113.08,30.83,'度')\n",
    "plt.grid()\n",
    "plt.savefig(r'./输出数据/样地坐标分布图.png',dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
